Genomics and proteomics research has identified biomarkers that can be used in the detection and treatment of many diseases. Disease assessment can be based on one or many biomarkers, and in some cases, different biomarkers may be appropriate for different disease stages. Such biomarkers can be used to assess disease progress and aid in determining treatment as well as in judging the effectiveness of a course of treatment. Accordingly, biomarker-based measurements permit improved patient care and inform about control of infection and disease spread.
Unfortunately, biomarker-based measurements can be slow, expensive, or otherwise impractical. Conventional methods used with biomarkers are typically based on gel electrophoresis, enzyme-linked immunosorbent assays (ELISAs), plasma resonance, or other techniques. These methods generally have limited sensitivity, slow response, and lack specificity. Thus, although biomarkers offer promise for improved disease treatment and diagnosis, these advantages have not been realized in practice.
The outbreak of new infectious diseases (e.g., SARS and avian influenza), and the emergence of drug resistant forms of old diseases (e.g., Staphylococcus aureus and Mycobacterium tuberculosis, M. tb) have heightened the need for global infectious disease surveillance as a tool to control the spread of infection, and guide therapeutic intervention. Tuberculosis (TB), a manageable disease only 20 years ago, has reemerged with alarming increases in mortality due to new drug resistant strains and co-infection with HIV. Technologies are needed to enable high throughput global surveillance of TB and other diseases; such surveillance would facilitate, for instance, accurate diagnosis of active infection and emergence of drug resistance.